| Jian X., Ahuja S., Nguyen T., Wu Q.M.J., “Design and Implementation of a Real-Time ellipse detection algorithm on a reconfigurable computer,” (In Progress). | |
| Ahuja S., Nguyen T., Wu Q.M.J., “Robust and Adaptive Path-planning for the Autonomous Robot Racing Challenge,” (In Progress). | |
| Nguyen T., Ahuja S., Wu Q.M.J., “An Integrated Image Segmentation Based on Combination of Markov Random Fields and Graph Cuts,” (In Progress). | |
| Ahuja S., Nguyen T., Wu Q.M.J., “Real-Time 3-D Location, Orientation and Tracking of Tools in a Work-Cell,” Auto 21 Poster Session, May 2009. | |
| Ahuja S., 2009, MASc. thesis, “Design and Implementation of a Real-time, Miniaturized Embedded Stereo Vision System (MESVS),” Dept. Elect. & Comp. Eng., Univ. of Windsor, Windsor, ON, Canada. | |
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Nguyen T., Ahuja S., Wu Q.M.J., “A Real-Time Ellipse Detection Based on Edge Grouping”, 2009 IEEE International Conference on Systems, Man, and Cybernetics (accepted). |
In this paper, we present a efficient algorithm for real-time ellipse detection. Unlike Hough transform algorithm that is computationally intense and requires a higher dimensional parameter space, our proposed method reduces the computational complexity significantly, and accurately detects ellipses in realtime. We present a new method of detecting arc-segments from the image, based on the properties of ellipse. We then group the arc-segments into elliptical arcs in order to estimate the parameters of the ellipse, which are calculated using the leastsquare method. Our method has been tested and implemented on synthetic and real-world images containing both complete and incomplete ellipses. The performance is compared to existing ellipse detection algorithms, demonstrating the robustness, accuracy and effectiveness of our algorithm. |
| Ahuja S., Wu Q.M.J., Internal Report, “Survey Paper on Smart Camera Architectures”, May 2009. | |
